Characteristics of Ovarian Cancer Immune Cell Invasion and Bioinformatics to Predict the Effect of Immunotherapy.

Recent studies have confirmed that tumor immune cell infiltration (ICI) is associated with sensitivity of ovarian cancer (OC) immunotherapy and disease progression of OC patients. However, studies related to immune infiltration in OC, has not been elucidated. Two algorithms are used to analyze the OC data in the TCGA and GEO databases. After combining the two data sets, the immune cell content of the sample was estimated by Cell-type Identification By Estimate Relative Subsets of RNA Transcripts (CIBERSORT method). An unsupervised consistent clustering algorithm was used to analyze ICI subtypes and their differentially expressed genes (DEGs). Two subgroups and three ICI gene clusters were identified by unsupervised consensus clustering algorithm. The ICI score was obtained by analyzing the gene characteristics through principal component analysis (PCA). The ICI score ranged from -15.8132 to 18.7211, which was associated with the prognosis of OC patients with immunotherapy. The Toll-like receptor pathway, B-cell receptor pathway, antigen processing and presentation pathway, NK-cell-mediated cytotoxicity pathway, and arginine-proline metabolism pathway were activated in the high ICI score group, suggesting that immune cells in the high ICI score group were activated, thus leading to a better prognosis in this group of patients. Patients with G3-G4 in the high ICI rating group were more sensitive to immunotherapy and had a better prognosis in patients with high tumor mutation burden (TMB). This study suggests that ICI scores can be used as a feasible auxiliary indicator for predicting the prognosis of patients with OC.

CDCA8 as an independent predictor for a poor prognosis in liver cancer.

BACKGROUND: Human cell division cycle associated 8 (CDCA8) a key regulator of mitosis, has been described as a potential prognostic biomarker for a variety of cancers, such as breast, colon and lung cancers. We aimed to evaluate the potential role of CDCA8 expression in the prognosis of liver cancer by analysing data from The Cancer Genome Atlas (TCGA). METHODS: The Wilcoxon rank-sum test was used to compare the difference in CDCA8 expression between liver cancer tissues and matched normal tissues. Then, we applied logistic regression and the Wilcoxon rank-sum test to identify the association between CDCA8 expression and clinicopathologic characteristics. Cox regression and the Kaplan-Meier method were used to examine the clinicopathologic features correlated with overall survival (OS) in patients from the TCGA. Gene set enrichment analysis (GSEA) was performed to explore possible mechanisms of CDCA8 according to the TCGA dataset. RESULTS: CDCA8 expression was higher in liver cancer tissues than in matched normal tissues. Logistic regression and the Wilcoxon rank-sum test revealed that the increased level of CDCA8 expression in liver cancer tissues was notably related to T stage (OR = 1.64 for T1/2 vs. T3/4), clinical stage (OR = 1.66 for I/II vs. III/IV), histologic grade (OR = 6.71 for G1 vs. G4) and histological type (OR = 0.24 for cholangiocarcinoma [CHOL] vs. hepatocellular carcinoma [LIHC]) (all P-values < 0.05). Kaplan-Meier survival analysis indicated that high CDCA8 expression was related to a poor prognosis in liver cancer (P = 2.456 × 10-6). Univariate analysis showed that high CDCA8 expression was associated with poor OS in liver cancer patients, with a hazard ratio (HR) of 1.85 (95% confidence interval [CI]: 1.47-2.32; P = 1.16 × 10-7). Multivariate analysis showed that CDCA8 expression was independently correlated with OS (HR = 1.74; CI: 1.25-12.64; P = 1.27 × 10-5). GSEA revealed that the apoptosis, cell cycle, ErbB, MAPK, mTOR, Notch, p53 and TGF-ß signaling pathways were differentially enriched in the CDCA8 high expression phenotype. CONCLUSIONS: High CDCA8 expression is a potential molecular predictor of a poor prognosis in liver cancer.

Correction to: ATF5 involved in radioresistance in nasopharyngeal carcinoma by promoting epithelial-to-mesenchymal phenotype transition.

The article ATF5 involved in radioresistance in nasopharyngeal carcinoma by promoting epithelial-to-mesenchymal phenotype transition, written by Yu Shuai, Erxi Fan, Qiuyue Zhong, Guangyong Feng, Qiying Chen, Xiaoxia Gou, Guihai Zhang, was originally published.

ATF5 involved in radioresistance in nasopharyngeal carcinoma by promoting epithelial-to-mesenchymal phenotype transition.

PURPOSE: This study aimed to investigate the effects of activating transcription factor-5 (ATF5) on nasopharyngeal carcinoma (NPC) cell radioresistance. METHODS: HONE-1 nasopharyngeal carcinoma cells were irradiated by conventional fractionation to generate HONE-1R radiotherapy-resistant cells. Short hairpin RNA (shRNA) expression plasmids targeting the ATF5 gene were constructed and transfected into the HONE-1R cell line. The proliferation assay, colony formation analysis, Transwell Boyden chamber assay and other experimental methods were performed to verify changes in the radiosensitivity and other biological of NPC cells. RESULTS: X-ray irradiation significantly promoted the upregulation of ATF5 protein levels in HONE-1 cells, and the protein expression of ATF5 increased with the dose of X-ray irradiation (p < 0.05). The colony formation rate, cell survival rate and migration ability of HONE-1R cells were significantly higher than those of HONE-1 cells (p < 0.05). Simultaneously, X-ray could also promote the morphology of epithelial-mesenchymal transition (EMT) in HONE-1 cells, inducing a lower expression level of E-cadherin and a higher expression level of N-cadherin in a dose-dependent manner (p < 0.05). Inhibiting ATF5 significantly reduced the colony formation rate, cell survival rate, migration and invasiveness of HONE-1R cells (p < 0.05). Moreover, sensitizing HONE-1R cells to X-ray irradiation significantly upregulated the expression of E-cadherin and downregulated the expression of N-cadherin in these cells (p < 0.05). CONCLUSIONS: ATF5 may be a potential therapeutic target to improve radiosensitivity in NPC.

Five genes as a novel signature for predicting the prognosis of patients with laryngeal cancer.

In this study, we purpose to investigate a novel five-gene signature for predicting the prognosis of patients with laryngeal cancer. The laryngeal cancer datasets were obtained from The Cancer Genome Atlas (TCGA). Both univariate and multivariate Cox regression analysis was applied to screening for prognostic differential expressed genes (DEGs), and a novel gene signature was obtained. The performance of this Cox regression model was tested by receiver operating characteristic (ROC) curves and area under the curve (AUC). Further survival analysis for each of the five genes was carried out through the Kaplan-Meier curve and Log-rank test. Totally, 622 DEGs were screened from the TCGA datasets in this study. We construct a five-gene signature through Cox survival analysis. Patients were divided into low- and high-risk groups depending on the median risk score, and a significant difference of the 5-year overall survival was found between these two groups (P < .05). ROC curves verified that this five-gene signature had good performance to predict the prognosis of laryngeal cancer (AUC = 0.862, P < .05). In conclusion, the five-gene signature consist of EMP1, HOXB9, DPY19L2P1, MMP1, and KLHDC7B might be applied as an independent prognosis predictor of laryngeal cancer.

A gene expression-based study on immune cell subtypes and glioma prognosis.

OBJECT: Glioma is a common malignant tumours in the central nervous system (CNS), that exhibits high morbidity, a low cure rate, and a high recurrence rate. Currently, immune cells are increasingly known to play roles in the suppression of tumourigenesis, progression and tumour growth in many tumours. Therefore, given this increasing evidence, we explored the levels of some immune cell genes for predicting the prognosis of patients with glioma. METHODS: We extracted glioma data from The Cancer Genome Atlas (TCGA). Using the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm, the relative proportions of 22 types of infiltrating immune cells were determined. In addition, the relationships between the scales of some immune cells and sex/age were also calculated by a series of analyses. A P-value was derived for the deconvolution of each sample, providing credibility for the data analysis (P < 0.05). All analyses were conducted using R version 3.5.2. Five-year overall survival (OS) also showed the effectiveness and prognostic value of each proportion of immune cells in glioma; a bar plot, correlation-based heatmap (corheatmap), and heatmap were used to represent the proportions of immune cells in each glioma sample. RESULTS: In total, 703 transcriptomes from a clinical dataset of glioma patients were drawn from the TCGA database. The relative proportions of 22 types of infiltrating immune cells are presented in a bar plot and heatmap. In addition, we identified the levels of immune cells related to prognosis in patients with glioma. Activated dendritic cells (DCs), eosinophils, activated mast cells, monocytes and activated natural killer (NK) cells were positively related to prognosis in the patients with glioma; however, resting NK cells, CD8+ T cells, T follicular helper cells, gamma delta T cells and M0 macrophages were negatively related to prognosis in the patients with glioma. Specifically, the proportions of several immune cells were significantly related to patient age and sex. Furthermore, the level of M0 macrophages was significant in regard to interactions with other immune cells, including monocytes and gamma delta T cells, in glioma tissues through sample data analysis. CONCLUSION: We performed a novel gene expression-based study of the levels of immune cell subtypes and prognosis in glioma, which has potential clinical prognostic value for patients with glioma.

Identification and potential mechanisms of a 4-lncRNA signature that predicts prognosis in patients with laryngeal cancer.

PURPOSE: This study aimed to describe the use of a novel 4-lncRNA signature to predict prognosis in patients with laryngeal cancer and to explore its possible mechanisms. METHODS: We identified lncRNAs that were differentially expressed between 111 tumor tissue samples and 12 matched normal tissue samples from The Cancer Genome Atlas Database (TCGA). We used Cox regression analysis to identify lncRNAs that were correlated with prognosis. A 4-lncRNA signature was developed to predict the prognosis of patients with laryngeal cancer. The receiver operating characteristic (ROC) curves and area under the curve (AUC) were used to verify the validity of this Cox regression model, and an independent prognosis analysis was used to confirm that the 4-lncRNA signature was an independent prognostic factor. Furthermore, the function of these lncRNAs was inferred using related gene prediction and Gene ontology (GO) enrichment analysis in order to clarify the possible mechanisms underlying their predictive ability. RESULTS: In total, 214 differentially expressed lncRNAs were identified, and a 4-lncRNA signature was constructed using Cox survival analysis. The risk coefficients in the multivariate Cox analysis revealed that LINC02154 and MNX1-AS1 are risk factors for laryngeal cancer, whereas MYHAS and LINC01281 appear to be protective factors. The results of a functional annotation analysis suggested that the mechanisms by which these lncRNAs influence prognosis in laryngeal cancer may involve the extracellular exosome, the Notch signaling pathway, voltage-gated calcium channels, and the Wnt signaling pathway. CONCLUSION: We identified a novel 4-lncRNA signature that can predict the prognosis of patients with laryngeal cancer and that may influence the prognosis of laryngeal cancer by regulating immunity, tumor apoptosis, metastasis, invasion, and other characteristics through the Notch signaling pathway, voltage-gated calcium channels, and the Wnt signaling pathway.